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Spring reads: Narrative structure of Pakistani literary fiction: How to get filthy rich in rising Asia and In other rooms, other wondors

An article in The New Yorker on Mohammed Hanif has touched me off on a spree of Pakistani novel reading.

I’ve gotten in a batch of 4 or 5 Pakistani novels of recent origin.  I’ve read 1 1/2 of them and some tropes are beginning to emerge.  Much as I noticed with South Korean Chaebol TV dramas, there is quite a bit of common structure in the genre.  Based on a statistical population of 2 novels:

  • [MH] How to Get Filthy Rich in Rising Asia, By Mohsin Hamid
  • [DM] In Other Rooms, Other Wonders by Daniyal Mueenuddin

Some observations:

There is an emphasis on cradle-to-grave narrative.  They are born, they grow up, they migrate, they procreate, they die.  It all ends in some crappy neighborhood in some version of Lahore.  The old ways and lands of the village give way to chaotic urbanization.  There is a total lack of urban planning.  There is a boss man.  There is a farm and lots of serfs.

There is a spunky lass of humble origin who trades physical favors to climb socially.

[MH] Her looks would not traditionally have been considered beautiful.  No milky complexion, raven tresses, bountiful bosom, or soft, moon-like face for her.  Her skin is darker than average, her hair and eyes lighter, making all three features a strikingly similar shade of brown.  This bestows on her a smoky quality, as though she has been drawn with charcoal.  She is also lean, tall, and flat-chested, her breasts the size, as your mother notes dismissively, of two cheap little squashed mangoes.

People get what’s coming to them, without a lot of soul-searching.

[DM] “I did you wrong”, said the robber weakly. “I know that.  You don’t know my life, just as I don’t know yours.  Even I don’t know what brought me here.  Maybe you’re a poor man, but I’m much poorer than you.  My mother is old and blind, in the slums outside Multan.  Make them fix me, ask them to and they’ll do it.”  He began to cry, not wiping the tears, which drew lines on his dark face.   “Go to hell”, said Nawab, turning away.  “Men like you are good at confessions.  My children would have begged in the streets.”

Everybody is kissing up to somebody.

[DM] “Sir, as you know, your lands stretch from here to the Indus, and on these lands are fully seventeen tube wells, and to tend these seventeen tube wells there is but one man, me, your servant.  In your service I have earned these gray hairs” – here he bowed his head to show the gray – “and now I cannot fulfill my duties as a I should.  Enough, sir, enough.  I beg you, forgive me my weakness.  Better a darkened house and proud hunger than a disgrace in the light of day.  Release me, I ask you, I beg you.”  The old man, well accustomed to these sorts of speeches, though not usually this florid, filed away at his nails and waited for the breeze to stop.  “What’s the matter, Nawabdin?”….”Well, sir, if I had a motorcycle, then I could somehow limp along, at least until I train up some younger man.”

Everybody is lording it over somebody.

[MH] Should the landlord or his sons drive by in their SUV, your father and his brothers will bring their hands to their foreheads, bend low, and avert their eyes.  Meeting the gaze of a landlord has been a risky business in these parts for centuries, perhaps since the beginning of history.

All junior employees eventually cheat in small or large ways their seniors.

[DM] “You better come inside”, said Mustafa.  He took her into a neat room, adorned with the fruits of his petty thefts, his inflated bills – a television and video player, a sewing machine covered with an embroidered cloth, a large garish clock with a plastic figure of a shepherdess that moved back and forth across the face – for like everyone else on the farm Mustafa trimmed out money where he could, a few rupees on the petrol, a bit of padding when he bought spare parts.

It all starts in the village.

[MH] The people of your village relieve themselves downstream of where they wash their clothes, a place in turn downstream of where they drink.  Farther upstream, the village before yours does the same.  Farther still, where the water emerges from the hills as a sometimes-gushing brook, it is partly employed in the industrial processes of an old, rusting, and subscale textile plant, and partly used as drainage for the fart-smelling gray effluent that results.

You can get far if you know how to bake a good chapatti.

[DM] At lunch she made the chapattis – no one in the village could do that properly.  Hassan came into the big hot kitchen, which had a row of coal-burning hearths set at waist level in one wall…He pinched Saleema under her arm as she stood flattening the chapattis between her hands.  “Here’s where the real meat is.”  He laughed without mirth, a drawn-out wheeze.

Medical care is terrible and ad hoc.  The most frequent natural cause of death is cancer, followed by snake bites.

[MH] When the pretty girl’s death comes it is mercifully swift, at diagnosis her cancer having spread from her pancreas throughout her body.  Her doctor is surprised that she is in so good a superficial state.

[DM] Two nights later Jaglani died.  The cancer had sperad to his lymph nodes and to his brain, and he died in great pain, despite the morphine.

All in all a rather grim tableau.  The overall set of tropes is quite different from the set of tropes involved in South Korean chaebol fiction, but there is that sense of hearing the same kind of story told over and over in slightly different voices.  So it’s a story that rings true and bears repetition within the culture.

Currently remaining on the stack:

  • [MH2] A case of exploding mangoes, by Mohammed Hanif
  • [ES] Sandokan: The Tigers of Mompracem, by Emilio Salgari

Also I will get, per suggestion of Khalid:

  • Omar Hamid’s “The Prisoner”
  • Saad Shafqat’s “Breath of Death”

To do: Exclude retired forecasters

I just noted looking at my last GITREP that @einsteinjs is still getting picked up based on success rate.  His forecasts are stale, however, as he quit a month or so ago.

To do:  Add a filter which excludes forecasters who have had no activity in over a month.  Not forecasts, which can be stand-pat and over a month old, just trying to factor out inactive forecasters who are either retired from the game or only logged in once.

This should produce some interesting shifts in the numbers and increase forecast quality.